14094 Zip Code Historical Type of Heating Fuel in a House Data
ACS 2010-2014 data
| 14094 Zip Code | New York | U.S. |
Total Housing Units | 20,596, 100% | 7,255,528 | 116,211,092 |
Utility Gas | 14,894, 72.32%, see rank | 56.12% | 48.85% |
Bottled, Tank, or LP Gas | 1,123, 5.45%, see rank | 3.36% | 4.86% |
Electricity | 2,535, 12.31%, see rank | 10.26% | 36.68% |
Fuel Oil, Kerosene, etc. | 1,564, 7.59%, see rank | 26.24% | 5.86% |
Coal or Coke | 5, 0.02%, see rank | 0.26% | 0.12% |
Wood | 314, 1.52%, see rank | 2.04% | 2.12% |
Solar Energy | 0, 0.00%, see rank | 0.03% | 0.05% |
Other Fuel | 129, 0.63%, see rank | 0.97% | 0.47% |
No Fuel Used | 32, 0.16%, see rank | 0.72% | 1.00% |
ACS 2008-2012 data
| 14094 Zip Code | New York | U.S. |
Total Housing Units | 20,843, 100% | 7,230,896 | 115,226,802 |
Utility Gas | 15,014, 72.03%, see rank | 54.92% | 49.42% |
Bottled, Tank, or LP Gas | 959, 4.60%, see rank | 3.16% | 5.03% |
Electricity | 2,602, 12.48%, see rank | 9.44% | 35.51% |
Fuel Oil, Kerosene, etc. | 1,665, 7.99%, see rank | 28.80% | 6.46% |
Coal or Coke | 11, 0.05%, see rank | 0.26% | 0.12% |
Wood | 341, 1.64%, see rank | 1.96% | 2.08% |
Solar Energy | 0, 0.00%, see rank | 0.02% | 0.04% |
Other Fuel | 197, 0.95%, see rank | 0.86% | 0.43% |
No Fuel Used | 54, 0.26%, see rank | 0.57% | 0.90% |
US Census 2000 data
| 14094 Zip Code | New York | U.S. |
Total Housing Units | 20,455, 100% | 7,056,860 | 105,480,101 |
Utility Gas | 14,841, 72.55%, see rank | 51.75% | 51.22% |
Bottled, Tank, or LP Gas | 871, 4.26%, see rank | 3.37% | 6.52% |
Electricity | 2,222, 10.86%, see rank | 8.72% | 30.35% |
Fuel Oil, Kerosene, etc. | 2,195, 10.73%, see rank | 33.11% | 8.97% |
Coal or Coke | 7, 0.03%, see rank | 0.14% | 0.14% |
Wood | 186, 0.91%, see rank | 1.17% | 1.68% |
Solar Energy | 0, 0.00%, see rank | 0.04% | 0.04% |
Other Fuel | 81, 0.40%, see rank | 1.04% | 0.39% |
No Fuel Used | 52, 0.25%, see rank | 0.66% | 0.69% |
* ACS stands for U.S. Census American Community Survey. According to the U.S. Census, if the date is a range, you can interpret the data as an average of the period of time.